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Record W1976002426 · doi:10.1115/ipc2014-33451

Application and Advancement of EMAT ILI Technologies for the Inspection of Cracks in Dents

2014· article· en· W1976002426 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsPetroleum Technology Alliance Canada
Fundersnot available
KeywordsPipeline (software)Deformation (meteorology)CrackingElectromagnetic acoustic transducerPipeline transportStress (linguistics)Forensic engineeringPetroleum engineeringEngineeringComputer scienceMarine engineeringMechanical engineeringConstruction engineeringStructural engineeringMaterials scienceAcousticsUltrasonic testingComposite materialUltrasonic sensorPhysics

Abstract

fetched live from OpenAlex

Pipeline dents and mechanical damage remain an integrity threat within the Oil & Gas pipeline industry. Such features typically consist of a localized deformation of the pipe wall. Under certain conditions, cracking may develop within or adjacent to the area of deformation due to stress concentration factors resulting from the deformation itself or from secondary damage such as a scrape or gouge. Conventional inline inspection technologies consistently to date have not explicitly addressed inspection capabilities for cracking within dents. This paper presents the results of a collaborative technical effort to assess and advance the abilities of EMAT inline inspection technologies to identify and characterize such mechanical damage features as found in liquid pipelines. The background and application of these advanced technologies for the targeted threats is discussed, as well as the experimental testing performed and results achieved.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.508
Threshold uncertainty score0.111

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.242
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations4
Published2014
Admission routes1
Has abstractyes

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